An Alternative Approach to ChIP-Seq Normalization Enables Detection of Genome-Wide Changes in Histone H3 Lysine 27 Trimethylation upon EZH2 Inhibition
November
An Alternative Approach to ChIP-Seq Normalization Enables Detection of Genome- Wide Changes in Histone H3 Lysine 27 Trimethylation upon EZH2 Inhibition
Brian Egan 0 1
Chih-Chi Yuan 1
Madeleine Lisa Craske 0 1
Paul Labhart 0 1
Gulfem D. Guler 1
David Arnott 1
Tobias M. Maile 1
Jennifer Busby 1
Chisato Henry 0 1
Theresa K. Kelly 0 1
Charles A. Tindell 1
Suchit Jhunjhunwala 1
Feng Zhao 1
Charlie Hatton 1
Barbara M. Bryant 1
Marie Classon 1
Patrick Trojer 1
0 Active Motif Inc., Carlsbad, California, United States of America, 2 Constellation Pharmaceuticals Inc., Cambridge, Massachusetts, United States of America, 3 Department of Molecular Oncology, Genentech Inc. , South San Francisco , California, United States of America, 4 Department of Protein Chemistry, Genentech Inc. , South San Francisco , California, United States of America, 5 Department of Bioinformatics, Genentech Inc. , South San Francisco, California , United States of America
1 Editor: Zhaohui Qin, Emory University Rollins School of Public Health , UNITED STATES
Chromatin immunoprecipitation and DNA sequencing (ChIP-seq) has been instrumental in inferring the roles of histone post-translational modifications in the regulation of transcription, chromatin compaction and other cellular processes that require modulation of chromatin structure. However, analysis of ChIP-seq data is challenging when the manipulation of a chromatin-modifying enzyme significantly affects global levels of histone post-translational modifications. For example, small molecule inhibition of the methyltransferase EZH2 reduces global levels of histone H3 lysine 27 trimethylation (H3K27me3). However, standard ChIP-seq normalization and analysis methods fail to detect a decrease upon EZH2 inhibitor treatment. We overcome this challenge by employing an alternative normalization approach that is based on the addition of Drosophila melanogaster chromatin and a D. melanogaster-specific antibody into standard ChIP reactions. Specifically, the use of an antibody that exclusively recognizes the D. melanogaster histone variant H2Av enables precipitation
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OPEN ACCESS
Funding: No specific funding was obtained for this
project. General funds from Constellation
Pharmaceuticals, Genentech Inc and Active Motif
Inc were used to support the work. The funders
provided support in the form of salaries for authors
[BE, CCY, MC, PL, GDG, DA, TMM JB, CH, TKK,
of D. melanogaster chromatin as a minor fraction of the total ChIP DNA. The D.
melanogaster ChIP-seq tags are used to normalize the human ChIP-seq data from DMSO and EZH2
inhibitor-treated samples. Employing this strategy, a substantial reduction in H3K27me3
signal is now observed in ChIP-seq data from EZH2 inhibitor treated samples.
Introduction
ChIP-seq is a powerful and commonly used technique for the detection of transcription factor
binding patterns and histone post-translational modification (PTM) occupancy profiles across
CAT, SJ, FZ, CH, BMB, MC, PT], but did not have
any additional role in the study design, data
collection and analysis, decision to publish, or
preparation of the manuscript. The specific roles of
these authors are articulated in the `author
contributions' section.
the entire genome [
1
]. ChIP-seq data in many different cell types and contexts have been used
to generate genome-wide chromatin modification maps that have provided significant insight
into the general relationship between transcriptomic and epigenomic landscapes [
2, 3
]. These
cell type comparisons have revealed substantial lineage-related differences in the profiles of
specific histone PTMs across genomes. However, manipulation of a given biological context,
such as comparisons of knockdown or knockout of individual histone modifying enzymes or
their respective inhibition with small molecules, may potentially involve subtle alterations to
the PTM landscape rather than resulting in a completely different pattern. Therefore, in recent
years, more complex statistical methods, software programs and computational models have
been developed in an attempt to adequately compare ChIP-seq data sets and reliably reveal the
differences [4±7].
Identifying differences between data sets becomes more challenging when differences are
not just occurring at specific sites across the genome, but involves global modification changes.
An example would be a setting where an increase or decrease of a particular histone PTM
occurs at all or most occupied sites across the genome, as is frequently the case when studying
the effects of chromatin modifying enzyme inhibitors. Impairing the function of a histone
methyltransferase (HMT) can result in a reduction in bulk methylation levels at the targeted
histone residue, which in the case of H3K27 methylation affects a large part of the genome. In
these instances, currently available bioinformatic-based normalization methods are not
applicable since they assume invariance in the signal to noise ratio, the background (...truncated)